Stochastic tensor complementarity problem with discrete distribution
DOI10.1007/S10957-021-01997-7zbMath1485.15033OpenAlexW4210568647MaRDI QIDQ2116609
Liyuan Cui, Shou-qiang Du, Yuan-Yuan Chen, Yi-Min Wei
Publication date: 18 March 2022
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10957-021-01997-7
convergencesemismooth Newton methodBarzilai-Borwein stepsizestochastic tensor complementarity problem
Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33) Random matrices (algebraic aspects) (15B52) Multilinear algebra, tensor calculus (15A69)
Related Items (4)
Cites Work
- Unnamed Item
- Unnamed Item
- Positive-definite tensors to nonlinear complementarity problems
- Tensor complementarity problem and semi-positive tensors
- Global uniqueness and solvability for tensor complementarity problems
- Properties of solution set of tensor complementarity problem
- Symmetric nonnegative tensors and copositive tensors
- Formulating an \(n\)-person noncooperative game as a tensor complementarity problem
- Robust solution of monotone stochastic linear complementarity problems
- Feasible semismooth Newton method for a class of stochastic linear complementarity problems
- Solution of monotone complementarity problems with locally Lipschitzian functions
- A penalized Fischer-Burmeister NCP-function
- \(\mathrm{P}\)-tensors, \(\mathrm{P}_0\)-tensors, and their applications
- An iterative method for finding the least solution to the tensor complementarity problem
- A continuation method for tensor complementarity problems
- Tensor absolute value equations
- Expected residual minimization method for monotone stochastic tensor complementarity problem
- Acceptable solutions and backward errors for tensor complementarity problems
- A lower dimensional linear equation approach to the m-tensor complementarity problem
- Bounds of the solution set of the tensor complementarity problem
- Tensor complementarity problems. I: Basic theory
- Tensor complementarity problems. II: Solution methods
- Tensor complementarity problems. III: Applications
- Stochastic structured tensors to stochastic complementarity problems
- A quadratically convergent algorithm for finding the largest eigenvalue of a nonnegative homogeneous polynomial map
- Properties of some classes of structured tensors
- A nonsmooth version of Newton's method
- Stochastic \(R_0\) tensors to stochastic tensor complementarity problems
- A mixed integer programming approach to the tensor complementarity problem
- Eigenvalues of a real supersymmetric tensor
- Exceptionally regular tensors and tensor complementarity problems
- A New Nonsmooth Equations Approach to Nonlinear Complementarity Problems
- Optimization and nonsmooth analysis
- Two-Point Step Size Gradient Methods
- A special newton-type optimization method
- Newton and Quasi-Newton Methods for a Class of Nonsmooth Equations and Related Problems
- Semismooth Karush-Kuhn-Tucker Equations and Convergence Analysis of Newton and Quasi-Newton Methods for Solving these Equations
- Nonmonotone Spectral Projected Gradient Methods on Convex Sets
- Tensor complementarity problems: the GUS-property and an algorithm
- Convergence Analysis of Some Algorithms for Solving Nonsmooth Equations
- Modified gradient dynamic approach to the tensor complementarity problem
- Theory and Computation of Complex Tensors and its Applications
- Expected Residual Minimization Method for Stochastic Linear Complementarity Problems
This page was built for publication: Stochastic tensor complementarity problem with discrete distribution
